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Data Warehouse ETL Testing & Data Quality Management A-Z
Highest Rated
Rating: 4.5 out of 5(8,573 ratings)
29,271 students

Data Warehouse ETL Testing & Data Quality Management A-Z

ETL Testing and Data Quality Management for beginners with practical exercises and certificate of completion.
Created byLorenz D.
Last updated 4/2019
English

What you'll learn

  • Understand the basics of ETL/ELT testing
  • The importance of Data Quality within the Data Lifecycle
  • Learn the different types of ETL/ELT testing and Data Quality dimensions
  • Design a set of frequently used ETL/ELT and Data Quality regression tests
  • A comparison of Data Quality tools (Informatica, Talend, Oracle, SAS)
  • Perform database tests using queries and build database views to automate ETL/ELT testing and Data Quality monitoring
  • Data Quality Management and monitoring
  • Setting up a database connection to your visualization tool
  • Build Data Quality dashboards and reports

Course content

4 sections20 lectures1h 52m total length
  • Introduction5:11
  • What is ETL/ELT Testing and Data Quality Management?4:48

    Explore how ETL and ELT testing ensures data quality and governance across a data warehouse, staging area, and data marts, testing transformations, lineage, and schema integrity from source to target.

  • Data Categories and Classifications7:38
  • Data Quality Rules and Dimensions6:32
  • Data Requirements and Test Design - Exercise4:22
  • Quiz

Requirements

  • Some basic knowledge of SQL
  • Some basic knowledge of visualization tools is recommended, but not required
  • Database setup (PostgreSQL, Oracle, SQL Server etc.) is recommended
  • Visualization setup (Qlik, Spotfire, Microstrategy, Tableau, PowerBI etc.) is recommended

Description

Learn the essentials of ETL Data Warehouse Testing and Data Quality Management through this step-by-step tutorial. This course takes you through the basics of ETL testing, frequently used Data Quality queries, reporting and monitoring. In this tutorial we will learn how to build database views for Data Quality monitoring and build Data Quality visualizations and reports!

..Learn to build data quality dashboards from scratch!

..Learn some of the most common mistakes made when performing ETL/ELT tests..

..Forget about manual ad-hoc ETL testing, learn more about automated ETL and data quality reports

The course contains training materials, where you can practice, apply your knowledge and build an app from scratch. The training materials are provided in an Excel file that you can download to your computer. Each module also ends with a short quiz and there is a final quiz at the end of the course.

After completion of this course, you will receive a certificate of completion.

Good luck and hope you enjoy the course.

Pre-requisites:

  • Basic knowledge of SQL

  • Some experience with Visualization tools would be helpful, but not required

  • Basic setup of database (PostgreSQL, Oracle) and visualization tool (Qliksense) is recommended

Course content:

The course consists of the following modules:

  • Introduction

  • What is ETL/ELT Testing and Data Quality Management?

  • Build database views for Data Quality Monitoring

  • Build dashboards for Reporting

  • Exercises

  • Final Quiz

Who should follow this course?

  • Students that want to learn the basics of ETL/ELT testing and Data Quality Management

  • Business Analysts and Data Analysts that would like to learn more about ETL/ELT testing, frequently used queries and practical examples

  • Software Engineers that would like to build an automated solution for ETL/ELT testing using database views/dashboards

  • Data Stewards and Managers considering to apply data quality standards within their organization


Who this course is for:

  • Students that want to learn the basics of ETL/ELT testing and Data Quality Management
  • Business Analysts and Data Analysts that would like to learn more about ETL/ELT testing, frequently used queries and practical examples
  • Software Engineers that would like to build an automated solution for ETL/ELT testing using database views/dashboards
  • Data Stewards and Managers considering to apply data quality standards within their organization